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Google’s ‘Project Nightingale’ Triggers Federal Inquiry
Google’s project with the country’s second-largest health system to collect detailed health information on 50 million American patients sparked a federal inquiry and criticism from patients and lawmakers. The data on patients of St. Louis-based Ascension were until recently scattered across 40 data centers in more than a dozen states.
(The Wall Street Journal)
Head of Microsoft AI and Research Harry Shum Is Leaving the Company
Microsoft Executive Vice President Harry Shum (Shen Xiangyang), the head of Microsoft AI and Research, will leave the tech giant in early 2020. A Microsoft spokesperson confirmed the departure of the 23-year Microsoft veteran, who will continue advising CEO Satya Nadella and company co-founder Bill Gates.
(Synced)
Elon Musk Picks Berlin for Tesla’s Europe Gigafactory
Elon Musk said Tuesday during an awards ceremony in Germany that Tesla’s European gigafactory will be built in the Berlin area. “There’s not enough time tonight to tell all the details,” Musk said during an on stage interview with Volkswagen Group CEO Herbert Diess. “But it’s in the Berlin area, and it’s near the new airport.”
(TechCrunch)
Seminal Debate: Yoshua Bengio | Gary Marcus — Live Streaming
This is the debate the AI world has been waiting for. Yoshua Bengio, the Turing Award owner and Gary Marcus, Founder of Robust.AI are going to have a debate on December 23, 2019.
(Live Streaming)
Technology
Kaolin: A PyTorch Library for Accelerating 3D Deep Learning Research
Researchers present Kaolin, a PyTorch library aiming to accelerate 3D deep learning research. With functionality to load and preprocess several popular 3D datasets, and native functions to manipulate meshes, pointclouds, signed distance functions, and voxel grids, Kaolin mitigates the need to write wasteful boilerplate code.
(NVIDIA & Mila & Universite de Montreal & McGill University & Vector Institute & University of Toronto) / (GitHub)
Making an Invisibility Cloak: Real World Adversarial Attacks on Object Detectors
In this work, researchers present a systematic study of adversarial attacks on state-of-the-art object detection frameworks. Using standard detection datasets, they train patterns that suppress the objectness scores produced by a range of commonly used detectors, and ensembles of detectors.
(Facebook AI & University of Maryland)
Neurons Spike Back
This article retraces the history of artificial intelligence through the lens of the tension between symbolic and connectionist approaches. From a social history of science and technology perspective, it seeks to highlight how researchers, relying on the availability of massive data and the multiplication of computing power have undertaken to reformulate the symbolic AI project.
(Sciences Po médialab & Zentrum Marc Bloch)
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Japanese Scientist Insists His Robot Twin Is Not Creepy
In an exclusive interview with Synced, Professor Hiroshi Ishiguro shared his thoughts on humanoids, human nature, human-robot interaction, knowledge and intelligence. The interview has been edited for brevity and clarity.
(Synced)
Texas A&M and Simon Fraser Universities Open-Source RL Toolkit for Card Games
Researchers from Texas A&M University and Canada’s Simon Fraser University have open-sourced a toolkit called “RLCard” for applying RL research to card games. The RLCard toolkit supports card game environments such as Blackjack, Leduc Hold’em, Dou Dizhu, Mahjong, UNO, etc. to bridge reinforcement learning and imperfect information games.
(Synced)
Global AI Events
December 2-6: AWS re:Invent 2019 in Las Vegas, United States
December 8-14: 2019 Conference on Neural Information Processing Systems (NeurIPS 2019) in Vancouver, Canada
January 7-10: CES 2020 in Las Vegas, United States
February 7-12: AAAI 2020 in New York, United States
Global AI Opportunities
Alan Turing Institute Safe and Ethical AI Research Fellow/Fellow
Research Scientist, Google Brain Toronto
OpenAI Seeking Software Engineers and Deep Learning Researchers
DeepMind Scholarship: Access to Science
Postdoctoral Researcher (AI) — Self-Supervised Learning
